What are the effective features of consultation? A mixed methods approach

Consultation is an integral part of many Educational Psychologist’s (EPs) work. Yet there is a large heterogeneity in understanding and use of this tool. Such diversity makes evaluating its efficacy difficult. This research therefore sought to identify what the effective features of consultation are by linking observed features to changes in agreed outcomes for children and young people (CYP). Mixed methods were employed to explore what EPs believe are the key features of consultation, what the barriers to effective consultation are, what happens in a consultation for a child or young person, and what combination of features can be identified in consultations which lead to positive changes for CYP.To explore EP views towards the effective features of consultation, 30 EPs were interviewed. Observable features of consultation were tallied for six consultations. For those consultations, goals were identified by participants and a baseline rating was given for each goal using Target Monitoring Evaluation (TME) forms. There were 10 goals identified. Change for these goals was recorded through completing the same form 6-8 weeks later, to allow analysis of which combination of features were present for children with differing progress towards outcomes. This was assessed using Qualitative Comparative Analysis (QCA). The most effective features of consultation, as identified by EPs, included the expert knowledge EPs have, the collaborative nature of consultation, and creating a shared understanding of the CYP and context for all participants. Consultations which were most likely to see positive change for CYP were ones in which the consultation was not dominated by gaining an understanding of the presenting problem. These results give clarity as to what the features of an effective consultation are through a mixed methods analysis. The findings have implications for EPs who use consultation, as well as consultees and those whom consultations are for.

What are the effective features of consultation? A mixed methods analysis

Consultation is an integral part of many Educational Psychologist’s (EPs) work. Yet there is a large heterogeneity in understanding and use of this tool. Such diversity makes evaluating its efficacy difficult. This research therefore sought to identify what the effective features of consultation are by linking observed features to changes in agreed outcomes for children and young people (CYP). Mixed methods were employed to explore what EPs believe are the key features of consultation, what the barriers to effective consultation are, what happens in a consultation for a child or young person, and what combination of features can be identified in consultations which lead to positive changes for CYP. To explore EP views towards the effective features of consultation, 30 EPs were interviewed. Observable features of consultation were tallied for six consultations. For those consultations, goals were identified by participants and a baseline rating was given for each goal using Target Monitoring Evaluation (TME) forms. There were 10 goals identified. Change for these goals was recorded through completing the same form 6-8 weeks later, to allow analysis of which combination of features were present for children with differing progress towards outcomes. This was assessed using Qualitative Comparative Analysis (QCA). The most effective features of consultation, as identified by EPs, included the expert knowledge EPs have, the collaborative nature of consultation, and creating a shared understanding of the CYP and context for all participants. Consultations which were most likely to see positive change for CYP were ones in which the consultation was not dominated by gaining an understanding of the presenting problem. These results give clarity as to what the features of an effective consultation are through a mixed methods analysis. The findings have implications for EPs who use consultation, as well as consultees and those whom consultations are for.

Within-Canopy Distribution of Stenoma catenifer (Lepidoptera: Elachistidae) Infestation in Avocado Orchards

Native to the neotropics, the avocado seed moth Stenoma catenifer Walsingham (Lepidoptera: Elachistidae) is a specialist pest of the family Lauraceae and considered one of the most important pests of avocados worldwide. However, little is known regarding its spatial distribution within a single tree. Therefore, we designed a study to evaluate the effects of canopy height and aspect (i.e., side of the tree) on fruit infestation by S. catenifer larvae in avocados. The study was conducted in three commercial organic avocado orchards located in São Paulo, Brazil. At each orchard, 40 fruit from 30 random trees were sampled weekly from October 2017 through February 2018, evaluating the number of fruits infested by S. catenifer larvae at three tree heights (bottom, middle, and top). In addition, fruits on the ground were also sampled. We also evaluated the effect of the side of the tree where the fruits were collected, i.e., whether they were on the side facing the east (sunrise) or the west (sunset). Within the avocado canopy, the level of fruit infestation by S. catenifer larvae was significantly higher at the top of the trees than in the middle and bottom. Fruit on the ground had lower levels of infestation than those on the tree canopy. The level of fruit infestation was also higher on the side of avocado trees facing the east (sunrise). Understanding the within-tree distribution of S. catenifer will help to better target monitoring and control activities against this pest in avocados.

Design and Validation of a Reflectarray Antenna with Optimized Beam for Ground Target Monitoring with a DVB-S-Based Passive Radar

A reflectarray antenna with an optimized sectorial beam is designed for the surveillance channel of a DVB-S-based passive radar (PR). The employment of satellite illuminators requires a high gain antenna to counteract the losses due to the great distance from the transmitter, but without forgetting a beamwidth wide enough to provide angular coverage. A method based on optimizing the position of several contiguous beams is proposed to achieve the required sectorial pattern. Different reflectarray elements are designed to achieve S-curves with smooth slopes and covering all the required phases (the S-curve represents the reflection phase of a single element, as a function of size, rotation and incidence angle). The real phase and modulus of the reflection coefficient of each element are considered in the optimization process to achieve the best real prototype. Geometry has been studied and adapted to employ commercial elements for the feed, feed-arm and the structure that holds the aperture. The designed prototype has been characterized in an anechoic chamber achieving a stable gain greater than 19 dBi in almost the complete DVB-S band, from 10.5 GHz to 12 GHz with a sectorial beam of 8.7∘×5.2∘. The prototype has also been validated in PR trials in terrestrial scenarios allowing the detection of cars at distances up to 600 m away from the PR, improving the performance achieved with commercial parabolic dish antennas.

Research on Design of Intelligent Background Differential Model for Training Target Monitoring

The detection of moving targets is to detect the change area in a sequence of images and extract the moving targets from the background image. It is the basis. Whether the moving targets can be correctly detected and segmented has a huge impact on the subsequent work. Aiming at the problem of high failure rate in the detection of sports targets under complex backgrounds, this paper proposes a research on the design of an intelligent background differential model for training target monitoring. This paper proposes a background difference method based on RGB colour separation. The colour image is separated into independent RGB three-channel images, and the corresponding channels are subjected to the background difference operation to obtain the foreground image of each channel. In order to retain the difference of each channel, the information of the foreground images of the three channels is fused to obtain a complete foreground image. The feature of the edge detection is not affected by light; the foreground image is corrected. From the experimental results, the ordinary background difference method uses grey value processing, and some parts of the target with different colours but similar grey levels to the background cannot be extracted. However, the method in this paper can better solve the defect of misdetection. At the same time, compared with traditional methods, it also has a higher detection efficiency.

Neural signatures of vigilance decrements predict behavioural errors before they occur

There are many monitoring environments, such as railway control, in which lapses of attention can have tragic consequences. Problematically, sustained monitoring for rare targets is difficult, with more misses and longer reaction times over time. What changes in the brain underpin these ‘vigilance decrements’? We designed a multiple-object monitoring (MOM) paradigm to examine how the neural representation of information varied with target frequency and time performing the task. Behavioural performance decreased over time for the rare target (monitoring) condition, but not for a frequent target (active) condition. This was mirrored in neural decoding using magnetoencephalography: coding of critical information declined more during monitoring versus active conditions along the experiment. We developed new analyses that can predict behavioural errors from the neural data more than a second before they occurred. This facilitates pre-empting behavioural errors due to lapses in attention and provides new insight into the neural correlates of vigilance decrements.

Energy-Efficient Ultrasonic Water Level Detection System with Dual-Target Monitoring

This study presents a developed ultrasonic water level detection (UWLD) system with an energy-efficient design and dual-target monitoring. The water level monitoring system with a non-contact sensor is one of the suitable methods since it is not directly exposed to water. In addition, a web-based monitoring system using a cloud computing platform is a well-known technique to provide real-time water level monitoring. However, the long-term stable operation of remotely communicating units is an issue for real-time water level monitoring. Therefore, this paper proposes a UWLD unit using a low-power consumption design for renewable energy harvesting (e.g., solar) by controlling the unit with dual microcontrollers (MCUs) to improve the energy efficiency of the system. In addition, dual targeting to the pavement and streamside is uniquely designed to monitor both the urban inundation and stream overflow. The real-time water level monitoring data obtained from the proposed UWLD system is analyzed with water level changing rate (WLCR) and water level index. The quantified WLCR and water level index with various sampling rates present a different sensitivity to heavy rain.